Critically ill patients are often unable to speak as a result of respiratory tract intubation for airway management and mechanical ventilation, which can be a traumatic life event that is frightening, reducespatient participation in care and decision-making, and impairs pain and symptom assessment. No large-scale communication intervention studies have been conducted in the intensive care unit (ICU) setting. To date, no studies have tested the effectiveness of teaching nurses to be facilitative communication partners of temporarily nonspeaking patients in ICU settings. The specific aims of this study are to (1) test the impact of two experimental interventions: (a) basic communication skills training (BCST) for nurses and (b) AAC techniques and education for nurses with individualized speech language pathologist consultation (AAC/SLP), on the ease, quality, frequency, and success of communications between nurses and nonspeaking ICU patients. (2) Compare the effects of BCST and AAC-SLP training with a control (usual care) cohort. This study is a prospective field experiment using a quasi-experimental cohort design conducted in two intensive care units, medical ICU and cardiothoracic ICU. The sample will be equally distributed between units. Three cohorts of 30 patient participants each and their respective nurse caregivers will be enrolled as participants (10 RNs for each cohort; 30 total nurses, and 90 total nurse-patient dyads). Conditions will be implemented in sequential order (control, BCST, AAC-SLP) to prevent contamination from other intervention conditions and to systematically investigate the effect of the intervention components. Trained observers will measure the frequency of nurse facilitative behaviors (quality), number of communication exchanges (frequency), number of successful exchanges, and rate communication ease across 4 observation sessions (2 per day) with each nurse-patient dyad. Primary covariates include severity of illness, level of consciousness, and physical restraint use. Statistical analysis will involve hierarchical generalized linear modeling (HGLM) by outcome groups and planned group comparisons using linear contrasts within the context of the HGLM.